This thesis investigates methods for automatic colour transfer when working withgeodata and possible metrics to evaluate the results. Several methods for colourtransfer as well as methods to create an objective measurement were tested. Themethod was evaluated by using a subjective score which was generated by surveyingeight people working with geodata. In the survey the participants were askedto “Rank the images from most similar to least similar, with what you imagine theresult would have been if you would have made the colour transfer manually”.The method with the best overall performance in this study was using colourtransfer in the CIEl colour space. This method was only matched by a methodsegmenting the image first based on colour information. As the method had thehighest average subjective score but a larger standard deviation than other methods.This was suspected to be largely due to the deviation in quality of the segmentationalgorithm. Using a different method for segmenting the image thismethod might perform even better.The objective measurements proposed in this study were not found to have aconsistent correlation with the subjective measurement, with the exception ofgradient structural similarity. Other methods could have a use in some cases butnot as general colour transfer objective measurement, though a larger study andmore data would be needed to confirm the findings.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-180167 |
| Date | January 2021 |
| Creators | Ågren, Anton |
| Publisher | Linköpings universitet, Datorseende |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0055 seconds